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api.py

@@ -23,6 +23,10 @@ app.add_middleware(
 
 ROOT = Path("/tmp/veureu")
 ROOT.mkdir(parents=True, exist_ok=True)
+TEMP_ROOT = Path("/tmp/temp")
+TEMP_ROOT.mkdir(parents=True, exist_ok=True)
+VIDEOS_ROOT = Path("/tmp/data/videos")
+VIDEOS_ROOT.mkdir(parents=True, exist_ok=True)
 
 @app.get("/")
 def root():
@@ -41,6 +45,37 @@ async def process_video(
     result = process_video_pipeline(str(tmp_video), config_path=config_path, out_root=out_root, db_dir=db_dir)
     return JSONResponse(result)
 
+@app.post("/create_initial_casting")
+async def create_initial_casting(
+    video: UploadFile = File(...),
+    epsilon: float = Form(...),
+    min_cluster_size: int = Form(...),
+):
+    # Guardar vídeo en carpeta de datos
+    video_name = Path(video.filename).stem
+    dst_video = VIDEOS_ROOT / f"{video_name}.mp4"
+    with dst_video.open("wb") as f:
+        shutil.copyfileobj(video.file, f)
+
+    # Crear estructura de carpetas en temp/<uploaded-video>/...
+    base = TEMP_ROOT / video_name
+    for sub in ("sources", "faces", "voices", "backgrounds"):
+        (base / sub).mkdir(parents=True, exist_ok=True)
+
+    # Aquí en el futuro se puede disparar la lógica real de detección
+    return {
+        "ok": True,
+        "video": str(dst_video),
+        "epsilon": float(epsilon),
+        "min_cluster_size": int(min_cluster_size),
+        "temp_dirs": {
+            "sources": str(base / "sources"),
+            "faces": str(base / "faces"),
+            "voices": str(base / "voices"),
+            "backgrounds": str(base / "backgrounds"),
+        },
+    }
+
 @app.post("/load_casting")
 async def load_casting(
     faces_dir: str = Form("identities/faces"),